Visualizing Latent Space with Python
Latent space refers to an abstract multi-dimensional space containing feature values that we cannot interpret directly,
but which encodes a meaningful internal representation of externally observed events.
The latent space is simply a representation of compressed data in which similar data points are closer together in space.
I plotted Latent Space on a 2D space and demonstrated how similar images are clustered in the latent space with Python model.
You are welcome to provide your comments and subscribe to my KZread channel.
The Python code is uploaded into github.com/AIMLModeling/Laten...
Пікірлер: 11
Thank You Very Much, Sir. Please could you also a part II video that explains how we provide latent space vector values into a model as input and how using those inputs a model can build a NEW image.
thanks for this
thank you so much
thank you very much. I'm curios, is it possible to know the specific patterns the program was able to identify or learn in order for the program to cluster the images according to their similarities?
Also When I proceed LS_visualize, no images are poped up and I can only see the grey box..
How plot can print out the result? mode 'plot' doesn't have h5 model...
Hi, would it be possible to use an array of transformation matrices to then plot these in 2D?
@statisticsandriskmodeling5477
Жыл бұрын
Yes, it is possible to use an array of transformation matrices to plot the transformed shapes in 2D.
Could you share the link of personal github for downloading the code?
@statisticsandriskmodeling5477
7 ай бұрын
The link is at the bottom of the description.
Can I use it for deepfakes